AI adoption without governance is a business risk

The risk is broader than the model

AI risk includes the information supplied to a system, the quality and appropriateness of outputs, automation authority, third-party dependencies, regulatory obligations and how people rely on results. Focusing only on model accuracy misses the surrounding business process.

Create a proportionate governance model

Not every AI use case needs the same review. A tool that summarizes a user’s own notes differs from an agent that makes decisions, changes records or communicates externally. Use risk tiers to scale evidence and approval requirements.

• Document purpose, owner, users and affected decisions.
• Assess data sources, permissions and sensitive information.
• Define human review and prohibited uses.
• Monitor quality, incidents, changes and ongoing value.
• Establish retirement and access-removal procedures.

Governance should enable responsible experimentation

Provide sandboxes, approved tools, reusable assessment templates and fast review for low-risk scenarios. When the safe path is clear and practical, teams are less likely to create shadow AI solutions.